Genetic Programming Theory and Practice III

✍ Scribed by Tina Yu, Rick Riolo, Bill Worzel (auth.), Tina Yu, Rick Riolo, Bill Worzel (eds.)

• Publisher: Springer US
• Year: 2006
• Tongue: English
• Leaves: 320
• Series: Genetic Programming 9
• Edition: 1
• Category: Library

✦ Synopsis

Genetic Programming Theory and Practice III explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). This contributed volume was developed from the third workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to this rapidly advancing field. The text provides a cohesive view of the issues facing both practitioners and theoreticians and examines the synergy between GP theory and application.

The foremost international researchers and practitioners in the GP arena contributed to the volume, discussing such topics as:

• techniques to enhance GP capabilities with real-world applications and real-world application success stories from a variety of domains, including chemical and process control, informatics, and circuit design
• visualization models to understand GP processing and
• open challenges facing the community and potential research directions

Genetic Programming Theory and Practice III provides the most recent developments in GP theory, practice, and the integration of theory and practice. This text, the result of an extensive dialog between GP theoreticians and practitioners, is a unique and indispensable tool for both academics and industry professionals interested in the GP realm.

✦ Table of Contents

Genetic Programming: Theory and Practice....Pages 1-14
Evolving Swarming Agents in Real Time....Pages 15-32
Automated Design of a Previously Patented Aspherical Optical Lens System by Means of Genetic Programming....Pages 33-48
Discrimination of Unexploded Ordnance from Clutter Using Linear Genetic Programming....Pages 49-64
Rapid Re-Evolution of an X-Band Antenna for Nasa’s Space Technology 5 Mission....Pages 65-78
Variable Selection in Industrial Datasets Using Pareto Genetic Programming....Pages 79-92
A Higher-Order Function Approach to Evolve Recursive Programs....Pages 93-108
Trivial Geography in Genetic Programming....Pages 109-123
Running Genetic Programming Backwards....Pages 125-140
An Examination of Simultaneous Evolution of Grammars and Solutions....Pages 141-158
The Importance of Local Search....Pages 159-175
Content Diversity in Genetic Programming and Its Correlation with Fitness....Pages 177-190
Genetic Programming Inside a Cell....Pages 191-206
Evolution on Neutral Networks in Genetic Programming....Pages 207-221
The Effects of Size and Depth Limits on Tree Based Genetic Programming....Pages 223-240
Application Issues of Genetic Programming in Industry....Pages 241-258
Challenges in Open-Ended Problem Solving with Genetic Programming....Pages 259-274
Domain Specificity of Genetic Programming Based Automated Synthesis: A Case Study with Synthesis of Mechanical Vibration Absorbers....Pages 275-290
Genetic Programming in Industrial Analog CAD: Applications and Challenges....Pages 291-306

✦ Subjects

Computing Methodologies; Artificial Intelligence (incl. Robotics); Theory of Computation; Algorithm Analysis and Problem Complexity; Programming Techniques